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Databases and Information Systems

2014

Articles 1 - 14 of 14

Full-Text Articles in Artificial Intelligence and Robotics

Towards Intelligent Caring Agents For Aging-In-Place: Issues And Challenges, Di Wang, Budhitama Subagdja, Yilin Kang, Ah-Hwee Tan Dec 2014

Towards Intelligent Caring Agents For Aging-In-Place: Issues And Challenges, Di Wang, Budhitama Subagdja, Yilin Kang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

The aging of the world’s population presents vast societal and individual challenges. The relatively shrinking workforce to support the growing population of the elderly leads to a rapidly increasing amount of technological innovations in the field of elderly care. In this paper, we present an integrated framework consisting of various intelligent agents with their own expertise and responsibilities working in a holistic manner to assist, care, and accompany the elderly around the clock in the home environment. To support the independence of the elderly for Aging-In-Place (AIP), the intelligent agents must well understand the elderly, be fully aware of the …

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Context-Aware Spelling Corrector For Sentiment Analysis, Dr. Muhammad Zubair Asghar, Fazal Masud Kundi Oct 2014

Context-Aware Spelling Corrector For Sentiment Analysis, Dr. Muhammad Zubair Asghar, Fazal Masud Kundi

Dr. Muhammad Zubair Asghar

One of the most thrived features of the Web 2.0 era is the fastest growing of user-generated content in the shape of blogs and reviews, with unmatched speed and size. These reviews contain poor, text quality and structure which results spelling mistakes as well as out-of-vocabulary words. This paper presents a Context-Aware Spelling Corrector for Sentiment Analysis based on similarity measures and statistical language model. The paper also presents some compelling statistics about spelling errors. The comparative results show that the proposed framework outperforms the related systems, features wise and in accuracy.

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Integrating Motivated Learning And K-Winner-Take-All To Coordinate Multi-Agent Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Janusz Starzyk, Yuan-Sin Tan, Loo-Nin Teow Aug 2014

Integrating Motivated Learning And K-Winner-Take-All To Coordinate Multi-Agent Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Janusz Starzyk, Yuan-Sin Tan, Loo-Nin Teow

Research Collection School Of Computing and Information Systems

This work addresses the coordination issue in distributed optimization problem (DOP) where multiple distinct and time-critical tasks are performed to satisfy a global objective function. The performance of these tasks has to be coordinated due to the sharing of consumable resources and the dependency on non-consumable resources. Knowing that it can be sub-optimal to predefine the performance of the tasks for large DOPs, the multi-agent reinforcement learning (MARL) framework is adopted wherein an agent is used to learn the performance of each distinct task using reinforcement learning. To coordinate MARL, we propose a novel coordination strategy integrating Motivated Learning (ML) …

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Integrating Motivated Learning And K-Winner-Take-All To Coordinate Multi-Agent Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Janusz Starzyk, Yuan-Sin Tan, Loo-Nin Teow Aug 2014

Integrating Motivated Learning And K-Winner-Take-All To Coordinate Multi-Agent Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Janusz Starzyk, Yuan-Sin Tan, Loo-Nin Teow

Research Collection School Of Computing and Information Systems

This work addresses the coordination issue in distributed optimization problem (DOP) where multiple distinct and time-critical tasks are performed to satisfy a global objective function. The performance of these tasks has to be coordinated due to the sharing of consumable resources and the dependency on non-consumable resources. Knowing that it can be sub-optimal to predefine the performance of the tasks for large DOPs, the multi-agent reinforcement learning (MARL) framework is adopted wherein an agent is used to learn the performance of each distinct task using reinforcement learning. To coordinate MARL, we propose a novel coordination strategy integrating Motivated Learning (ML) …

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Lexicon-Based Sentiment Analysis In The Social Web, Fazal Masud Kundi, Dr. Muhammad Zubair Asghar Jul 2014

Lexicon-Based Sentiment Analysis In The Social Web, Fazal Masud Kundi, Dr. Muhammad Zubair Asghar

Dr. Muhammad Zubair Asghar

Sentiment analysis is a compelling issue for both information producers and consumers. We are living in the “age of customer”, where customer knowledge and perception is a key for running successful business. The goal of sentiment analysis is to recognize and express emotions digitally. This paper presents the lexicon-based framework for sentiment classification, which classifies tweets as a positive, negative, or neutral. The proposed framework also detects and scores the slangs used in the tweets. The comparative results show that the proposed system outperforms the existing systems. It achieves 92% accuracy in binary classification and 87% in multi-class classification.

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Lexicon Based Approach For Sentiment Classification Of User Reviews, Dr. Muhammad Zubair Asghar Jul 2014

Lexicon Based Approach For Sentiment Classification Of User Reviews, Dr. Muhammad Zubair Asghar

Dr. Muhammad Zubair Asghar

With the advent of web, online user reviews are getting more and more attention of the researchers because valuable information about products and services are available on social media like twitter1. These reviews are very helpful for organizations as well as for new customers showing interest in these products or services. But this data is generated in tremendous amount which is out of control of manual mining methods. These reviews need a model that has the ability to gauge these shared reviews according to predefined categories. This work introduces a rule based approach to find the opinion classification of reviews. …

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Cenknn: A Scalable And Effective Text Classifier, Guansong Pang, Huidong Jin, Shengyi Jiang Jul 2014

Cenknn: A Scalable And Effective Text Classifier, Guansong Pang, Huidong Jin, Shengyi Jiang

Research Collection School Of Computing and Information Systems

A big challenge in text classification is to perform classification on a large-scale and high-dimensional text corpus in the presence of imbalanced class distributions and a large number of irrelevant or noisy term features. A number of techniques have been proposed to handle this challenge with varying degrees of success. In this paper, by combining the strengths of two widely used text classification techniques, K-Nearest-Neighbor (KNN) and centroid based (Centroid) classifiers, we propose a scalable and effective flat classifier, called CenKNN, to cope with this challenge. CenKNN projects high-dimensional (often hundreds of thousands) documents into a low-dimensional (normally a few …

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Direct Neighbor Search, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang Jun 2014

Direct Neighbor Search, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang

Kyriakos MOURATIDIS

In this paper we study a novel query type, called direct neighbor query. Two objects in a dataset are direct neighbors (DNs) if a window selection may exclusively retrieve these two objects. Given a source object, a DN search computes all of its direct neighbors in the dataset. The DNs define a new type of affinity that differs from existing formulations (e.g., nearest neighbors, nearest surrounders, reverse nearest neighbors, etc.) and finds application in domains where user interests are expressed in the form of windows, i.e., multi-attribute range selections. Drawing on key properties of the DN relationship, we develop an …

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Detection And Scoring Of Internet Slangs For Sentiment Analysis Using Sentiwordnet, Dr. Muhammad Zubair Asghar Jun 2014

Detection And Scoring Of Internet Slangs For Sentiment Analysis Using Sentiwordnet, Dr. Muhammad Zubair Asghar

Dr. Muhammad Zubair Asghar

The online information explosion has created great challenges and opportunities for both information producers and consumers. Understanding customer’s feelings, perceptions and satisfaction is a key performance indicator for running successful business. Sentiment analysis is the digital recognition of public opinions, feelings, emotions and attitudes. People express their views about products, events or services using social networking services. These reviewers excessively use Slangs and acronyms to express their views. Therefore, Slang's analysis is essential for sentiment recognition. This paper presents a framework for detection and scoring of Internet Slangs (DSIS) using SentiWordNet in conjunction with other lexical resources. The comparative results …

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Sentiment Classification Through Semantic Orientation Using Sentiwordnet, Dr. Muhammad Zubair Asghar, Dr, Auranzeb Khan Jun 2014

Sentiment Classification Through Semantic Orientation Using Sentiwordnet, Dr. Muhammad Zubair Asghar, Dr, Auranzeb Khan

Dr. Muhammad Zubair Asghar

Sentiment analysis is the procedure by which information is extracted from the opinions, appraisals and emotions of people in regards to entities, events and their attributes. In decision making, the opinions of others have a significant effect on customers ease in making choices regards to online shopping, choosing events, products, entities. In this paper, a rule based domain independent sentiment analysis method is proposed. The proposed method classifies subjective and objective sentences from reviews and blog comments. The semantic score of subjective sentences is extracted from SentiWordNet to calculate their polarity as positive, negative or neutral based on the contextual …

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Lexical Based Semantic Orientation Of Online Customer Reviews And Blogs-J-Am Sci 10(8) 143_147--07-June-2014.Pdf, Dr. Muhammad Zubair Asghar May 2014

Lexical Based Semantic Orientation Of Online Customer Reviews And Blogs-J-Am Sci 10(8) 143_147--07-June-2014.Pdf, Dr. Muhammad Zubair Asghar

Dr. Muhammad Zubair Asghar

Rapid increase in internet users along with growing power of online review sites and social media hasgiven birth to sentiment analysis or opinion mining, which aims at determining what other people think andcomment. Sentiments or Opinions contain public generated content about products, services, policies and politics.People are usually interested to seek positive and negative opinions containing likes and dislikes, shared by users forfeatures of particular product or service. This paper proposed sentence-level lexical based domain independentsentiment classification method for different types of data such as reviews and blogs. The proposed method is basedon general lexicons i.e. WordNet, SentiWordNet and user …

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Declarative-Procedural Memory Interaction In Learning Agents, Wenwen Wang, Ah-Hwee Tan, Loo-Nin Teow, Tan Yuan-Sin May 2014

Declarative-Procedural Memory Interaction In Learning Agents, Wenwen Wang, Ah-Hwee Tan, Loo-Nin Teow, Tan Yuan-Sin

Research Collection School Of Computing and Information Systems

It has been well recognized that human makes use of both declarative memory and procedural memory for decision making and problem solving. In this paper, we propose a computational model with the overall architecture and individual processes for realizing the interaction between the declarative and procedural memory based on self-organizing neural networks. We formalize two major types of memory interactions and show how each of them can be embedded into autonomous reinforcement learning agents. Our experiments based on the Toad and Frog puzzle and a strategic game known as Starcraft Broodwar have shown that the cooperative interaction between declarative knowledge …

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Exploring Customer Specific Kpi Selection Strategies For An Adaptive Time Critical User Interface, Ingo Keck, Robert J. Ross Jan 2014

Exploring Customer Specific Kpi Selection Strategies For An Adaptive Time Critical User Interface, Ingo Keck, Robert J. Ross

Conference papers

Rapid growth in the number of measures available to describe customer-organization relationships has presented a serious challenge for Business Intelligence (BI) interface developers as they attempt to provide business users with key customer information without requiring users to painstakingly sift through many interface windows and layers. In this paper we introduce a prototype Intelligent User Interface that we have deployed to partially address this issue. The interface builds on machine learning techniques to construct a ranking model of Key Performance Indicators (KPIs) that are used to select and present the most important customer metrics that can be made available to …

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An Exploratory Analysis Of Twitter Keyword-Hashtag Networks And Knowledge Discovery Applications, Ahmed A. Hamed Jan 2014

An Exploratory Analysis Of Twitter Keyword-Hashtag Networks And Knowledge Discovery Applications, Ahmed A. Hamed

Graduate College Dissertations and Theses

The emergence of social media has impacted the way people think, communicate, behave, learn, and conduct research. In recent years, a large number of studies have analyzed and modeled this social phenomena. Driven by commercial and social interests, social media has become an attractive subject for researchers. Accordingly, new models, algorithms, and applications to address specific domains and solve distinct problems have erupted. In this thesis, we propose a novel network model and a path mining algorithm called HashnetMiner to discover implicit knowledge that is not easily exposed using other network models. Our experiments using HashnetMiner have demonstrated anecdotal evidence …

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